This paper designs a measurement system of energy consumption for clothes model controlled by robot technology, the system uses DC motor regulated by PWM regulator to drive the worm wheel reducer and the sinusoidal mechanism, then to drive the robot legs to swing forward and backward in sinusoidal step. The sensors detect the rotation speed and torque of the sinusoidal mechanism, the power and energy consumption. The experiments show the system is high in accuracy, excellent in repetition, and suitable for the further research on the principle and evaluation system of the clothes energy consumption.

The processing mechanism of electrical discharge machining (EDM) is complex and there are many factors affecting it, therefore the process parameter is very important for processing quality. This paper analyses the relationship between electric parameter and processing quality, then uses support vector machine (SVM) to predict the optimum electric parameter. The simulation result shows that the highest prediction accuracy is 96.10%, the lowest is 89.20%, average accuracy is 94.28%, indicating that the algorithm stability and generalization ability are outstanding. Further verified by experiment, the highest prediction accuracy can amount to 92.65%, the lowest is 81.5%, average accuracy is 89.38%, and electric parameter optimized by SVM can guarantee the expected processing effect better. The exploration in EDM intelligent machining will be convenient for operators to determine the most effective machining conditions.

The machining parameter is very important for quality control in electrical discharge machining (EDM). This paper analysis the pit size in different electric parameter based on ANSYS, and then revises the simulation results according to the experiment test data. Taking advantage of numerical fitting methods to determine the relationship between electric parameters and machining quality. The experiments show the ratio of prediction to test for Vm , Ra , θ is 120.58%,108.18%,78.47% separately. The precision is higher and it can meet the need of the actual processing.

In order to meet the need of medicine packing industry for Mechanical Properties such as high speed and accuracy, the electronic granulation counter is developed. The counter consists of LED light source, double linear array CCD sensors TCD1209D, synchronously driving circuit for double linear array CCD based on CPLD EPM3064A, synchronously data acquisition card with A/D converter TLC 5510 of the high speed, and host computer. The test channel is 400 millimeter wide, the horizontal resolution is 0.1 millimeter, the driving frequency of linear array CCD sensors is 10 MHz and the vertical resolution is 0.3 millimeter, software binarization is effective for identifying the medicine tablets of different light transmittance. The experiments show the electronic granulation counter is accurate and reliable, counting speed is over 8000 per minute, and can distinguish the broken tablets and the overlap tablets.

In order to solve the problem of choosing vibration mode of the cylinder shell resonating density meter, this paper analysis the dynamics of the resonator by ANSYS. The modal analysis result shows that the transverse n=2 and n=3 all meet the requirement, the fluid-structure interaction result shows that the transverse n=2 is more sensitive to the changing of fuel density than n=3. Final analysis of the influence by temperature and pressure on the vibration frequency shows that the influence by pressure is very little which can be omitted, but the influence by temperature is remarkable and needs to be compensated. The conclusions and methods of finite element analysis can be used for resonant liquid density meter design.